ABSTRACT In this application, we propose to develop Hi-C technology and data analysis software for a user-friendly method to associate antimicrobial resistant (AMR) and virulence gene-containing mobile elements with their associated bacterial strains. Mobile elements are extra-chromosomal DNA or RNA molecules that encode functional elements. These molecules can be transmitted between members of the same species and across disparate species, leading to the rapid evolution of biochemical pathways through the sharing of mobile element-encoded proteins. This has a profound influence on the evolution of microbial communities, with particular impact on the drug resistance and virulence profiles of the members of the communities. To date, there is no cost-effective method for identifying mobile element hosts in a mixed microbial community: A significant fraction of microorganisms are unculturable under laboratory settings and current shotgun genomic methods fail to capture host information. Therefore, a new tool is needed to provide the information critical to understanding mobile element biology. Methods such as chromosome confirmation capture (3C) and Hi-C can be used rapidly and with high accuracy to identify DNA molecules that co-exist within individual cells directly from a mixed culture or biological sample. The goal of this proposal to develop a new class of tools that can be used to identify the hosts and transmission of mobile elements in a complex microbial community. The product proposed in this SBIR Phase II application addresses the need for rapid, culture-free identification of mobile element-host relationships in complex microbial communities. The method is built upon Phase Genomics? expertise with the use of Hi-C and 3C techniques, which allows to deconvolve complex mixtures of cells within microbial communities, without the need for laboratory culture. In this application, we propose to produce a method that reduces cost, increases speed, and simplifies the analysis of a proximity ligation-based test to associate plasmids with their host. Our approach is based on two discrete work packages: Aim 1 is focused on combining target enrichment and proximity-ligation methods to reduce sequencing costs associated with metagenomic deconvolution. In Aim 2, we will develop and design a customer-facing web portal for upload and analysis of data in which our clients can navigate easily. Upon completion of the proposed project, we will have laid the basis for a first-generation target enrichment Hi- C kit and service that will make our innovative platform commercially available.